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D-VELOP
Introduction to Natural Language Processing
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D-VELOP
Includes information on data analysis and visualization tools as well as links to recorded workshop series on various related topics.
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Data Visualization Workshop
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Introduction to Tableau (Summer 2021)
Data Visualization using Python (Matplotlib and Seaborn)
Data Visualization Using Python - Interactive Plots (Bokeh)
Data Visualization using Microsoft PowerPoint and Excel
Data Visualization with R Part 1: Intro to R
Data Visualization with R Part 2: Tidyverse/Tidy Data and dplyr
Data Visualization with R Part 3 - Web Scraping with OpenRefine API
Data Visualization with R Part 4: ggplot2
Data Visualization with R Part 5 - Sentiment Analysis
Data Visualization using Tableau (Summer 2020)
Machine Learning Workshop
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Introduction to Python
Machine Learning Overview (using Python)
Preparing your data for Machine Learning
Machine Learning using Matlab
Supervised Learning 1 - Linear Classifiers
Supervised Learning 2 - Tree Based Models
Application 1 - Sentiment Analysis
Application 2 - Dimensionality Reduction
Application 3 - Time Series Data
Unsupervised Learning - Clustering Analysis
Model Validation and Selection
Fairness and Bias in Machine Learning
Explainable AI - An Overview
Introduction to Reinforcement Learning
Machine Learning and Deep Learning Workshop - 2021
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Introduction to Neural Networks
Intro to Automated Machine Learning: Hyper-Parameter Tuning
Introduction to NLP part1 - text processing
Hyper-Parameter Tuning: Bayesian Optimization
Introduction to NLP Part 2 - Neural Networks
Introduction to Julia
Introduction to Computer Vision with Neural Networks
Intro to Python visualization tools: Seaborn and ipywidgets.
Data Scraping and Analysis with Python
Intro to Reinforcement Learning on an optimization perspective.
Machine Learning and Deep Learning Workshop - 2022
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Data Scraping and Analysis with Python
Introduction to Neural Networks
Introduction to Computer Vision with Neural Networks
Intro to Hyperparameter Optimization: Black-Box Optimization Approaches
Introduction to Generative adversarial networks (GANs)
Introduction to Recommender Systems
Intro to Parallel Computing
Introduction to Python in Data Science
Intro to Supervised and Unsupervised Machine Learning Algorithms
Data Scraping and Analysis with Python
Intro to Java and Algorithms Part 1
Intro to Java and Algorithms Part 2
Introduction to Nueral Network
Introduction to Web API and Database
Intro to RNN and LSTM
Introduction to Transformers in Image Processing
Intro to Hyperparameter Optimization: Bayesian Optimization
Machine Learning and Deep Learning Workshop - 2023
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Introduction to Python
Data Scraping and Analysis with Python
Introduction to Hadoop and Mapreduce
Introduction to Container and Kubernetes
Introduction to Federated Learning
Introduction to Python -2023 fall
Data visualization using Python
Introduction to PyTorch 1
Introduction to PyTorch 2
Introduction to Transformer Neural Network
Machine Learning and Deep Learning Workshop - 2024(Spring)
Machine learning for Audio
Intro to Multimodal in Machine Learning
Intro to Generative models
Intro to Contrastive Learning
Intro to Few-shot Learning
Machine Learning and Data Visualization Workshop - 2024(Fall)
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Introduction to Python
Introduction to PyTorch
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